1. Aliprantis, C.D., Burkinshaw, O.: Positive Operators. Springer, Berlin (2006)
2. Anil, C., Lucas, J., Grosse, R.: Sorting out Lipschitz function approximation. In: Proceedings of the 36th International Conference on Machine Learning, PMLR 97, pp. 291–301 (2019)
3. Appell, J., De Pascale, E., Vignoli, A.: Nonlinear Spectral Theory. Walter de Gruyter, Berlin (2008)
4. Asadi, K., Misra, D., Littman, M.: Lipschitz continuity in model-based reinforcement learning. In: Proceedings of the 35th International Conference on Machine Learning, PMLR 80, pp. 264–273 (2018)
5. Calabuig, J.M., Falciani, H., Sánchez Pérez, E.A.: Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets. Neurocomputing 398, 172–184 (2020)